Evaluating learning curves and competence in colorectal EMR among advanced endoscopy fellows: a pilot multicenter prospective trial using cumulative sum analysis. Academic Article uri icon

Overview

abstract

  • BACKGROUND AND AIMS: Data on colorectal EMR (C-EMR) training are lacking. We aimed to evaluate C-EMR training among advanced endoscopy fellows (AEFs) by using a standardized assessment tool (STAT). METHODS: This multicenter prospective study used a STAT to grade AEF training in C-EMR during their 12-month fellowship. Cumulative sum analysis was used to establish learning curves and competence for cognitive and technical components of C-EMR and overall performance. Sensitivity analysis was performed by varying failure rates. AEFs completed a self-assessment questionnaire to assess their comfort level with performing C-EMR at the completion of their fellowship. RESULTS: Six AEFs (189 C-EMRs; mean per AEF, 31.5 ± 18.5) were included. Mean polyp size was 24.3 ± 12.6 mm, and mean procedure time was 22.6 ± 16.1 minutes. Learning curve analyses revealed that less than 50% of AEFs achieved competence for key cognitive and technical C-EMR endpoints. All 6 AEFs reported feeling comfortable performing C-EMR independently at the end of their training, although only 2 of them achieved competence in their overall performance. The minimum threshold to achieve competence in these 2 AEFs was 25 C-EMRs. CONCLUSIONS: A relatively low proportion of AEFs achieved competence on key cognitive and technical aspects of C-EMR during their 12-month fellowship. The relatively low number of C-EMRs performed by AEFs may be insufficient to achieve competence, in spite of their self-reported readiness for independent practice. These pilot data serve as an initial framework for competence threshold, and suggest the need for validated tools for formal C-EMR training assessment.

publication date

  • September 19, 2020

Research

keywords

  • Colorectal Neoplasms
  • Gastroenterology

Identity

Scopus Document Identifier

  • 85097102631

Digital Object Identifier (DOI)

  • 10.1016/j.gie.2020.09.023

PubMed ID

  • 32961243

Additional Document Info

volume

  • 93

issue

  • 3